Strain-Based Design of Tubulars for Extreme-Service Wells
Bibliographic record
Abstract
Summary This paper presents a framework for a strain-based design of tubular strings in extreme-temperature or high-pressure/ high-temperature (HP/HT) wells. The relevant concepts are illustrated by examples from analytical and experimental investigation of a casing material considered for use in thermally stimulated wells operated by Shell Canada Limited (Shell) in western Canada. Much of this framework is also relevant to other applications where deformation-driven loading mechanisms are present. Strain-based design uses material capacity beyond its elastic range to overcome a number of economic and technical hurdles encountered in conventional load-based designs. It has been used successfully in field applications where plastic deformations occur (e.g., thermal wells and pipelines). However, current industry standards for material selection have their origins in load-based design. More sophisticated material-characterization tools are required for strain-based designs, in which post-yield material properties govern much of the system response. This paper describes the application of strain-based concepts to the design of casing strings under combined loading where some load components are deformation controlled. The paper emphasizes the need to address strain localization, high-strain cyclic plastic loading, strain-rate-dependent strength, and associated stress-relaxation effects. Strain-based design is most effective if relevant and reliable post-yield material properties are available. Experimental investigation of a candidate material considered for Shell Canada's thermal wells consisted of a series of custom-designed coupon-scale tests. The tests were conducted to acquire data describing the post-yield material response to monotonic and cyclic loading at temperatures ranging from 20 to 350°C. Conclusions of this paper summarize findings of the executed material-evaluation program, outline options to minimize strain-localization impacts, and provide recommendations for strain-based designs of well-completion tubulars. Following these recommendations should result in higher reliability and more cost-effective wells in completion programs using strain-based strategies for designs of extreme service wells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".